In the current information age, a big problem most people face is data overload, or information overload. A majority of information is carried by text data, or in the form of text contents such as documents, emails, web pages, news and blog articles, and user reviews, feedback, customer communication data such as survey, text messages, phone transcripts, etc., and the amount of such data is ever increasing day by day.
When information is contained in a large amount of scattered text data, finding the needed information can be difficult. For example, a user booking a hotel room may want to read reviews on the hotel. Some websites that host user reviews can have over hundreds or thousands of reviews written by many users over time for a specific hotel, and it is often virtually impossible for a user to read all the reviews to find the specific information he or she is looking. In some cases, the user may want to know what other users have said about a particular aspect, such as the room service, or the shuttle service of the hotel. But digging out information related to such topics from the numerous reviews can be very time-consuming by conventional search methods. Furthermore, even if the user is able to gather all the reviews on the specific topic of room service, there can be still be numerous comments from numerous users, with some giving the service a positive comment, while others may have given it a negative comment. If the user is particularly interested in knowing what negative comments other users have said about it, it could be more time-consuming to locate such information one by one.
Furthermore, a comment on a specific product or service can occur in many other places in addition to dedicated review websites. For example, some people may comment on their experience in a blog, or on a social network site, or reporters may cite certain opinions in a news article, etc., and in such cases, user comments, whether positive or negative, can be dispersed among a large number of other text contents, and locating specific comments from such sources can require much effort.
In addition to user reviews of products or services that contain user opinions, which may either be positive or negative, other types of information can also be contained in scattered text contents. For example, if a reader is reading a long medical document, and he wants to find out what drugs may have interaction with other drugs, it can also be a very time-consuming task to locate such information in the document one by one even if the reader is knowledgeable in the medical field.
Given such problems, it would be desirable if the computer system that displays the text contents to the reader can also provide a tool that can help the reader locate specific information quickly and accurately. For example, if the reader is reading user reviews of a hotel, it would be much more efficient if the site could provide a tool that lets the reader select a criterion and click a button, and then present all the information the reader is looking for in an easy-to-digest way.